Lab researcher's team shines in protein folding predictions

Charlie Strauss of the Lab ’s Bioscience Division and his colleague, Professor David Baker from the University of
Washington, participated in the experiment during the fourth Critical Assessment of Techniques for Protein Structure
Prediction (CASP4).

“This annual experiment is a delightful and terrifying phenomena for any protein scientist working on predicting protein
structure,” Strauss said. “Participants in the experiment are sent a list of proteins whose structures have been solved but
not made public. They are invited to stick their necks out and predict the structure of a true unknown. Then they and
their peers go to the conference and find out the answer. They are assigned grades,just like in school.”

The computational technique, co-authored by the Strauss and Baker group, is known as Rosetta. The software is based
upon the assumption that local sequence biases, but does not uniquely determine, the final structure. Predicted proteins
are assembled from short fragments taken from a database of known structures with similar local sequences. Rosetta
showed remarkable success in predicting the structure of folded proteins from its the linear sequence of amino acids.

“Some people call protein structure the second half of the genome project,” Strauss said. “Genes code for proteins, and a
unique property of proteins is that they derive their function from their structure. Structures begin to tell us what
proteins do, and how they do it, and we are developing ways to predict a protein ’s approximate structure from its
sequence. Billions of dollars are being spent worldwide on measuring protein structure, so doing it computationally is
obviously very desirable.”

There are between 10,000 and 100,000 important protein structures, but only a few thousand of these are currently
known. Strauss specializes in predicting novel structures, ones that have not previously been seen.

“Nature recycles her structural designs,” Strauss said. “Once we know all the important structures, any new proteins will
probably have structures similar to these, but so far we've only begun to get a sampling from direct measurement. So
getting ahead of the experimentalist and predicting the structure of proteins with previously unseen designs --the novel
folds – is a high value objective, not to mention the most fun and challenging. Predictions aren't nearly as good as
measurements, and assessing prediction success is a relative kind of thing.”

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